Total 32,223 skills, AI & Machine Learning has 5202 skills
Showing 12 of 5202 skills
Use at the start of any conversation - Determine how to find and use skills, requiring the skill tool to be invoked before any response (including clarification questions)
Vercel AI SDK 5 patterns. Trigger: When building AI chat features - breaking changes from v4.
This skill should be used when the user asks to "apply skill improvements", "update skill from plan", "execute improvement plan", "fix skill issues", "implement skill recommendations", or mentions applying improvements from quality review reports. Reads improvement-plan-{name}.md files generated by skill-quality-reviewer and intelligently merges and executes the suggested changes to improve Claude Skills quality.
Transcribe audio to text using local whisper.cpp. Use when user wants to convert audio/video to text, get transcription, or speech-to-text.
First obtain customer information and follow-up records, determine the product matching path, and output targeted sales strategies. Supports two product lines: Pre-sales Digital Employee and Langtum Platform.
Initialize Claude Code project settings with standard hooks and language-specific permissions. Use when setting up a new project for Claude Code or adding standard configuration to an existing project.
Give agents persistent structural memory of a codebase — navigate dependencies, track public APIs, and understand why connections exist without re-reading the whole repo.
Self-improve AI Factory skills based on project context, accumulated patches, and codebase patterns. Analyzes what went wrong, what works, and enhances skills to prevent future issues. Use when you want to make AI smarter for your project.
Access real-time, continuously refreshed investment context through the Primary Logic External API under /v1. Use when asked to power Codex, Claude Code, OpenClaw, or custom agents with LLM-ranked relevance and impact signals from podcasts, articles and news, X/Twitter, Kalshi, Polymarket, earnings calls, filings, and other monitored sources across public and private companies for decision support or user-controlled trading workflows.
Diseño de prompts para LLMs: system prompts, few-shot examples, chain-of-thought, RAG, structured outputs.
Generate high-divergence, out-of-the-box analysis plans and prompts that counter anchoring, mode collapse, and context bias while staying practical. Use when requests ask for unconventional strategies, non-obvious options, radical reframing, MCP-assisted synthesis across prior messages/sources, or "think differently" outputs that still require executable next steps.
Learn how to manage conversation context in AMCP to avoid LLM API errors from exceeding context windows. This skill covers SmartCompactor strategies, token estimation, configuration, and best practices.